Joriam - e/acc

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[Joriam - e/acc @JoriamMP]

AI isn't lessening the workload; it is enabling the current workforce to orchestrate more across the more technical, laborious tasks within large enterprises. Agentic systems are evolving faster than our current systems can modernize. In that case, are SMBs even more behind?

[Aaron Levie @levie]

Another week on the road meeting with a couple dozen IT and AI leaders from large enterprises across banking, media, retail, healthcare, consulting, tech, and sports, to discuss agents in the enterprise.

Some quick takeaways:

* Clear that we’re moving from chat era of AI to agents that use tools, process data, and start to execute real work in the enterprise. Complementing this, enterprises are often evolving from “let a thousand flowers bloom” approach to adoption to targeted automation efforts applied to specific areas of work and workflow.

* Change management still will remain one of the biggest topics for enterprises. Most workflows aren’t setup to just drop agents directly in, and enterprises will need a ton of help to drive these efforts (both internally and from partners). One company has a head of AI in every business unit that roles up to a central team, just to keep all the functions coordinated.

* Tokenmaxxing! Most companies operate with very strict OpEx budgets get locked in for the year ahead, so they’re going through very real trade-off discussions right now on how to budget for tokens. One company recently had an idea for a “shark tank” style way of pitching for compute budget. Others are trying to figure out how to ration compute to the best use-cases internally through some hierarchy of needs (my words not theirs).

* Fixing fragmented and legacy systems remain a huge priority right now. Most enterprises are dealing with decades of either on-prem systems or systems they moved to the cloud but that still haven’t been modernized in any meaningful way. This means agents can’t easily tap into these data sources in a unified way yet, so companies are focused on how they modernize these.

* Most companies are *not* talking about replacing jobs due to agents. The major use-cases for agents are things that the company wasn’t able to do before or couldn’t prioritize. Software upgrades, automating back office processes that were constraining other workflows, processing large amounts of documents to get new business or client insights, and so on. More emphasis on ways to make money vs. cut costs.

* Headless software dominated my conversations. Enterprises need to be able to ensure all of their software works across any set of agents they choose. They will kick out vendors that don’t make this technically or economically easy.

* Clear sense that it can be hard to standardize on anything right now given how fast things are moving. Blessing and a curse of the innovation curve right now - no one wants to get stuck in a paradigm that locks them into the wrong architecture. One other result of this is that companies realize they’re in a multi-agent world, which means that interoperability becomes paramount across systems.

* Unanimous sense that everyone is working more than ever before. AI is not causing anyone to do less work right now, and similar to Silicon Valley people feel their teams are the busiest they’ve ever been.

One final meta observation not called out explicitly. It seems that despite Silicon Valley’s sense that AI has made hard things easy, the most powerful ways to use agents is more “technical” than prior eras of software. Skills, MCP, CLIs, etc. may be simple concepts for tech, but in the real world these are all esoteric concepts that will require technical people to help bring to life in the enterprise.

This both means diffusion will take real work and time, but also everyone’s estimation of engineering jobs is totally off. Engineers may not be “writing” software, but they will certainly be the ones to setup and operate the systems that actually automate most work in the enterprise.

[Joriam - e/acc @JoriamMP]

https://t.co/Gy28dMyCDM

[Joriam - e/acc @JoriamMP]

For the builders out there, @Lovable is free for International Women's Day! Access and empowerment for all. I'll drop my build later today.

[Joriam - e/acc @JoriamMP]

Phenomenal resources

[Riti Kumari @riti2409]

Github repositories which would be really helpful for job preparation, upskilling and much more 🧵

[tobi lutke @tobi]

This is actually brilliant work by microsoft: https://t.co/X3StwYxXr6.

Sending mini WASM programs instead of prompts to LLM providers would be incredibly powerful. Multiturn, , Grammar, COT, RAG, function calling, etc could all massively benefit from this

[Extropic @extropic]

Mini podcast conversation between @GarryTan and our CEO (@GillVerd) + CTO (@trevormccrt1), discussing our unique approach to computing leveraging the stochastic physics of electrons.

[Alex Reibman 🖇️ @AlexReibman]

Got invited to a pre-New Years Eve party in SF…

But instead of partying, everyone was just hacking on startups and side projects. They were intense.

Here are some of the demos we saw from the party animals at @AGIHouseSF (🧵):

[Andrew Côté @Andercot]

"Restricting your speech back propagates to restricting your thoughts"

is the premise of 1984 and the reason why freedom of speech is so foundationally important to any democratic republic.

[Justine Moore @venturetwins]

Using ChatGPT in December 2023

[Trung Phan @TrungTPhan]

The comparison between GPT-4 and Google’s new Gemini LLM is fascinating

[Chamath Palihapitiya @chamath]

Looks like the heads of a few asset managers (errr, I mean universities) looked the other way when asked about genocide.

Expect the boards of these asset managers (errr, I mean universities) to feel a lot of pressure to act and fire them.

[Beff (e/acc) @beffjezos]

CAN YOU FEEL THE ACCELERATION, ANON?

[Henri Pierre-Jacques @hpierrejacques]

They are really trying to say there is racial discrimination for diverse VCs that target POC…this in an industry where 2% of funding goes to POC

The precedent and slippery slope we are on is terrifying

I have so many emotions so will process it first

https://t.co/aNx8SFNtJz

[Energy Transitions Commission @ETC_energy]

Our first #CriticalMinerals Factsheet looks at challenges of demand & supply for #Copper.

Copper demand is highly cross-cutting, as it is used in all clean energy tech. Two largest drivers are grids and EVs.

Mined output may need to rise from ~22Mt up to at least 30Mt in 2030.

[Danielle Fong 🔆 @DanielleFong]

good summary about the floaty rock drama so far

“if you’re not following LK99, you’re missing out on the most fun thing happening or the internet now. Feels like the old internet.”

https://t.co/ETlt031ObZ

[Financelot @FinanceLancelot]

Yellen was questioned about China suddenly dumping $859B US treasuries due to war

Few understand the US has already been preparing for this event which is why they're restricting the Dollar supply by destroying crypto exchanges, raising rates & have $2.5T in Reverse Repo waiting

[koko 𝑥𝑠 @kokoxs]

Is no one else freaking out about this 🤯

DoD’s new Office of Strategic Capital that has a Small Business Administration which is matching 2:1 private LP commitments towards deep tech funds

[Joriam - e/acc @JoriamMP]

Business as usual scenario will lead to the collapse of the Antarctic overturning circulation. Amplifying/positive feedback loops will make all this much more abysmal.

[Prof. Matt England @ProfMattEngland]

👉👉 Out today in @nature our new paper showing how meltwater increases around Antarctica are set to dramatically slowdown the Antarctic overturning circulation, with a potential collapse this century. https://t.co/p3au6k4zcK A🧵on how this work came about and what we found...

[Michael Thomas @curious_founder]

Clean energy critics often argue that addressing climate change will require too much mining.

So I looked into the data.

I found that our current fossil fuel economy requires 535x more mining than a 100% clean energy economy would.

🧵

[Alberto Romero @Alber_RomGar]

Before ChatGPT and GPT-4, life was quiet. Now I can't help but see what's approaching fast.

Behind Richard Sutton's Bitter lesson, there's a Bitterer one. Something that ChatGPT accelerated and GPT-4 made apparent. And I don't think we can escape it in any way: